Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jmylchreest/aide --skill recallgit clone --depth 1 https://github.com/jmylchreest/aideWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jmylchreest/aide/recall)<a href="https://agentmods.dev/skills/jmylchreest/aide/recall"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/recall/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jmylchreest/aide/recall"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.00788 |
| Opus 5 | $0.00010 | $0.00394 |
| Sonnet 5 | $0.00004 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recall
Recommended model tier: balanced (sonnet) - this skill performs straightforward operations
Search stored memories and decisions to answer questions about past learnings, architectural choices, patterns, and project context.
MCP Tools
Search Memories
| Tool | Purpose |
|---|---|
mcp__plugin_aide_aide__memory_search |
Full-text search (fuzzy, prefix, substring matching) |
mcp__plugin_aide_aide__memory_list |
List memories, optionally filtered by category |
Get Decisions
| Tool | Purpose |
|---|---|
mcp__plugin_aide_aide__decision_get |
Get specific decision by topic |
mcp__plugin_aide_aide__decision_list |
List all decisions |
mcp__plugin_aide_aide__decision_history |
Get all versions of a decision |
Workflow
- Parse the question - Extract key terms
- Search both sources:
- Use
mcp__plugin_aide_aide__memory_searchwith relevant keywords - Use
mcp__plugin_aide_aide__decision_getwith the topic, ormcp__plugin_aide_aide__decision_list
- Use
- Analyze timestamps - Prefer most recent (ULIDs are time-ordered)
- Answer - Combine relevant context from both sources
Instructions
When the user asks about previous context:
-
For architectural/design questions (testing, auth, database, etc.):
- Use
mcp__plugin_aide_aide__decision_getwith topic (e.g., "testing") - If unsure of topic name, use
mcp__plugin_aide_aide__decision_list
- Use
-
For learnings/patterns/gotchas:
- Use
mcp__plugin_aide_aide__memory_searchwith query (e.g., "ESM imports")
- Use
-
When answering:
- Cite the source (memory or decision)
- Include the date for context
- Note if something was updated/changed
Examples
User: "What testing framework did we decide on?"
→ Use mcp__plugin_aide_aide__decision_get with topic="testing"
→ Answer with the decision and rationale
User: "What was the issue with ESM imports?"
→ Use mcp__plugin_aide_aide__memory_search with query="ESM imports"
→ Answer with the learning
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 91 lines · 19 tokens per session scan A f89d08062a16
recall is a skill published in the GitHub repository jmylchreest/aide (17 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 788 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
durable-session-state
Persist plans, scope decisions, evidence, and reviewer/critic verdicts to durable files during long or multi-phase tasks so work survives context compaction, session resumes, and handoffs. Use for swarm-mode tasks, before context grows large, when recording approval gates, and when resuming after compaction or a…
continuous-learning
Use when a mistake, correction, or surprise taught the workspace something that must stick — a retro or postmortem, the same agent error corrected twice, a resolved bug's root cause, scattered notes-to-self — and route that lesson to the durable surface that fires next time. NOT a forward choice with alternatives…
claude-compaction-restore
Use when a Claude Code session has just compacted, is about to compact, reached context limit, resumed after /compact, or needs to rebuild its working mental model from Claude JSONL transcripts and touched files.
init
Turn on Rekal memory in the current repository by running rekal init. Use when the user asks to initialize or set up Rekal here, or when a rekal command reported the repository is not initialized. Once per repository. Do not offer this merely because a repo lacks a .rekal/ store — most repos do not want one.
install
Install the Rekal binary on this machine. Use when rekal is not on PATH — a command reported command not found — or when the user asks to install Rekal. Once per machine, not per repository; to set up a repo that already has the binary, use the init skill instead.
atomic-wiki
Conversational wiki and capture-bucket routing. Fires when the user wants a place, space, or folder for notes, research, tickets, raw dumps, or knowledge capture — checks the block in /.claude/CLAUDE.md; if the cwd is under a registered realm, creates the folder as a bucket via atomic wiki bucket add rather than a…